CN114997990A - Distributed account checking method, device and system - Google Patents
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Abstract
The invention provides a distributed account checking method, a device and a system, which can be applied to the financial field or other fields. The distributed reconciliation method comprises the following steps: receiving transaction stream splitting data from a master server; the transaction flow splitting data is generated by splitting the transaction flow data by the total server according to a preset grouping quantity; sorting the transaction flow splitting data according to key values in the transaction flow splitting data; performing parallel ladder-type reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file; and sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file. The invention can use low-cost physical resources to achieve the best performance support and adapt to the development of business diversity.
Description
Technical Field
The invention relates to the field of finance, in particular to a distributed reconciliation method, device and system.
Background
The transaction information generated on line is recorded in a local database by the transaction pipeline system, and each reconciliation period (such as every day) is checked with the transaction details provided by an external system one by one, and the reconciliation is carried out according to the difference to ensure the financial balance.
The transaction flow of large banks reaches over hundred million levels every day, several hours are spent for completing daily account checking, the requirement on resources (application and database resources) of an account checking system is high, and the expansion capability is low. With the development of business volume and the expansion of business diversity, the cost of optimizing reconciliation on the basis of the original architecture is very high.
In the prior art, an initiating side system or a service side system generally realizes account checking, the account checking system leads the transaction flow of the opposite side into a local database, and the two tables of the database are respectively checked. If the data in the table 1 in the reconciliation period is obtained, the records in the table 2 are searched one by one for checking, then the data in the table 2 is obtained, and the data in the table 1 is checked one by one; some systems mark the retrieval result during the first check, and although the number of second checks is reduced, a large amount of updating operation is increased. The requirement of hundreds of millions of data quantity on database resources is high, the retrieval efficiency is low due to the fact that the data quantity is large and the support degree of parallel processing is not high, and hundreds of millions of accounts are usually checked for hours.
Disclosure of Invention
The embodiments of the present invention mainly aim to provide a distributed reconciliation method, apparatus and system, so as to achieve the best performance support by using low-cost physical resources, and adapt to the development of business diversity.
In order to achieve the above object, an embodiment of the present invention provides a distributed reconciliation method, including:
receiving transaction stream splitting data from a master server; the transaction flow splitting data is generated by splitting the transaction flow data by the total server according to a preset grouping quantity;
sorting the transaction flow splitting data according to key values in the transaction flow splitting data;
performing parallel ladder-type reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file;
and sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
In one embodiment, the transaction pipeline split data comprises a first transaction pipeline split data and a second transaction pipeline split data;
performing parallel ladder reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result split file comprises the following steps:
matching the key values of the sorted first transaction flow splitting data with the key values of the sorted second transaction flow splitting data;
when the matching is successful, checking account according to the account checking content corresponding to the key value to obtain an account checking content split file;
when the matching fails, obtaining a single-side difference split file according to a comparison result of the key values of the sorted first transaction flow split data and the key values of the sorted second transaction flow split data;
and splitting the file according to the account checking content and the unilateral difference split file to obtain the account checking result split file.
In one embodiment, sorting the transaction pipeline split data according to key values in the transaction pipeline split data includes:
carrying out secondary splitting on the transaction flow split data to obtain each transaction flow subdata;
sequencing the transaction flow subdata according to the key values;
and selecting merged transaction flow data from the first transaction flow data in the sequenced transaction flow sub data according to the key value, and then putting the merged transaction flow data into a transaction flow split data file for corresponding cyclic processing to obtain the sequenced transaction flow split data.
An embodiment of the present invention further provides a distributed reconciliation apparatus, including:
the receiving module is used for receiving transaction flow splitting data from the main server; the transaction flow splitting data is generated by splitting the transaction flow data by the total server according to a preset grouping quantity;
the sorting module is used for sorting the transaction flow splitting data according to key values in the transaction flow splitting data;
the reconciliation module is used for carrying out parallel ladder reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file;
and the sending module is used for sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
In one embodiment, the transaction pipeline split data comprises a first transaction pipeline split data and a second transaction pipeline split data;
the reconciliation module comprises:
the matching unit is used for matching the key values of the sorted first transaction pipeline splitting data with the key values of the sorted second transaction pipeline splitting data;
the account checking unit is used for checking the account according to the account checking content corresponding to the key value to obtain an account checking content split file;
the unilateral difference split file unit is used for obtaining a unilateral difference split file according to a comparison result of the key values of the sorted first transaction flow split data and the key values of the sorted second transaction flow split data when the matching fails;
and the reconciliation result split file unit is used for splitting the file according to the reconciliation content and the unilateral difference split file to obtain a reconciliation result split file.
In one embodiment, the sorting module comprises:
the secondary splitting unit is used for carrying out secondary splitting on the transaction flow split data to obtain each transaction flow subdata;
the sequencing unit is used for sequencing the transaction flow sub data according to the key values;
and the circulating unit is used for selecting merged transaction pipeline data from the first transaction pipeline data in the sequenced transaction pipeline data according to the key values, and then putting the merged transaction pipeline data into the transaction pipeline split data file for corresponding circulating processing to obtain the sequenced transaction pipeline split data.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of the distributed reconciliation method when executing the computer program.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the distributed reconciliation method.
Embodiments of the present invention further provide a computer program product, which includes a computer program/instruction, and when the computer program/instruction is executed by a processor, the steps of the distributed reconciliation method are implemented.
An embodiment of the present invention further provides a distributed reconciliation system, including:
a plurality of distributed account checking devices as described above, which are applied to the sub-servers; and
the main server is used for splitting the transaction flow data according to a preset grouping quantity to obtain transaction flow split data and sending the transaction flow split data to the sub-servers; and merging the reconciliation result split files from the plurality of sub-servers to obtain a reconciliation result file.
The distributed reconciliation method, the device and the system of the embodiment of the invention sort according to the key values in the transaction flow split data, perform parallel ladder-type reconciliation according to the key values in the sorted transaction flow split data and the corresponding reconciliation contents to obtain the reconciliation result split file, and send the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flow chart of a distributed reconciliation method in an embodiment of the present invention;
FIG. 2 is a schematic diagram of a distributed reconciliation method in another embodiment of the invention;
FIG. 3 is a block diagram of an overall server in an embodiment of the invention;
FIG. 4 is a schematic diagram of data allocation in an embodiment of the invention;
fig. 5 is a flowchart of S102 in the embodiment of the present invention;
FIG. 6 is a schematic diagram of secondary splitting and sorting in an embodiment of the invention;
FIG. 7 is a schematic illustration of a sort merge according to an embodiment of the present invention;
fig. 8 is a flowchart of S103 in the embodiment of the present invention;
FIG. 9 is a diagram of key value matching in an embodiment of the present invention;
fig. 10 is a block diagram of a distributed reconciliation apparatus in an embodiment of the present invention;
FIG. 11 is a block diagram of the structure of a computer device in an embodiment of the present invention;
fig. 12 is a schematic diagram of a distributed reconciliation system in an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
In the technical scheme of the invention, the data acquisition, storage, use, processing and the like all conform to relevant regulations of national laws and regulations.
It should be noted that the distributed reconciliation method, device and system of the present invention can be used in reconciliation scenes in the financial field, and can also be used in any fields except the financial field. The embodiment of the invention does not limit the application fields of the distributed reconciliation method, the device and the system.
The terms involved in the present invention are explained as follows:
checking accounts: the transaction flow recording system and the flow details provided by the external system carry out the verification process of the transaction details. For example, the bank payment system checks the daily recorded flow with transaction records provided by the bank core or external clearing organization, and performs reconciliation and other processing on the difference flow according to business rules.
In view of the low support degree of parallel processing and low retrieval efficiency in the prior art, embodiments of the present invention provide a distributed reconciliation method, apparatus and system, which rely on a database based on a file format, support parallel and distributed processing, can achieve optimal performance processing under relatively small resources, and adapt to the development of business diversity.
The reconciliation needs at least two systems, for example, the payment mechanism interacts with the bank through a clearing organization, and the transaction flow of the payment mechanism recorded by the clearing organization as an initiator and the real customer flow recorded by the bank as an issuer need to carry out both-side reconciliation clearing. For convenience of description, the present invention defines the initiator as system a and the server as system B, and realizes A, B reconciliation of the two systems.
A. The system B respectively outputs transaction running files in the same reconciliation period (generally consistent with the clearing period), the files output by the system A, B are filtered and grouped through a certain algorithm, the files are split into N relatively small files, the small files are respectively sorted and checked, a summarizing result file and a difference file are output, finally the files output by the small files are respectively merged, the merged summarizing result file and the combined difference file are the files output by the reconciliation module, and reconciliation and clearing can be carried out according to the two files. The reconciliation and clearing process is outside the scope of the present invention.
The invention provides algorithm support for grouping, and ensures that the same transaction flow can be distributed to the same group, so as to realize the same group reconciliation of small files; the grouped small files support parallel processing for sequencing and account checking and also support distributed processing (a plurality of servers run simultaneously), so that the best performance support can be achieved by using low-cost physical resources; the data summarization only summarizes the summarization result and the reconciliation difference, the required resources are very small, and the data summarization is a centralized processing mode. As the initiator system and the server system have own scene settings, the difference of the formats of the generated transaction pipeline files is relatively large, so that the analysis adaptation of the file formats needs to be customized. Different demand scenarios have different requirements for account checking, and file analysis and filtering are required according to actual requirements. For example, if the transaction flow document only includes a transaction success record, it is only necessary to check key element matching (comparing transaction flow numbers), transaction amounts, and the like, but if the transaction flow document also includes a failure record, it is also necessary to check elements such as transaction states. The present invention will be described in detail below with reference to the accompanying drawings.
Fig. 1 is a flowchart of a distributed reconciliation method in an embodiment of the present invention. Fig. 2 is a schematic diagram of a distributed reconciliation method in another embodiment of the invention. As shown in fig. 1-2, the distributed reconciliation method comprises:
s101: transaction pipeline split data is received from the master server.
The transaction flow splitting data is generated by splitting the transaction flow data by the total server according to a preset grouping number.
When the system is specifically implemented, the main server performs adaptive analysis and filtering on transaction flow files from the system A and the system B, acquires key value keys (such as transaction flow numbers) capable of identifying unique records and key elements needing account checking, such as transaction states and transaction amounts, and then performs grouping according to the key value keys to generate a plurality of small files. The same group of small files for both systems is the smallest unit of parallel and distributed computation afterwards.
The source file provides many data items, and the filtering ensures that the generated small file (transaction stream splitting data) only retains key values key, account checking elements, the record line number of the source file and the like. All the subsequent processing is performed based on the grouped small files, if all the data are reserved, the processing complexity is brought by the uncertainty of the format, and the use amount of the memory is increased by too many data items.
Fig. 3 is a schematic grouping diagram of the overall server in the embodiment of the present invention. As shown in fig. 3, a process of parsing a source file into a plurality of small files (transaction stream split data) is called grouping, and the number of the split small files is the number of the grouping and needs to be set in advance after evaluation according to actual performance requirements and resource conditions. The grouping algorithm may use hash modulo or consistent hash, but cannot group in a random manner because the grouping algorithm needs to ensure that records of the same key value key are definitely assigned to the same group. For example, the packets are grouped by using a hash (hash) modulo algorithm, if the preset number of the packets is 64, after the key value key is analyzed, the hash of the key is used to modulo the 64, and 64 small files can be generated according to the modulo result (0-63). The source files provided by the system A and the system B must use the same grouping algorithm, so that the grouped data of the two systems can be ensured to correspond according to the grouping numbers.
Fig. 4 is a schematic diagram of data allocation in an embodiment of the invention. As shown in fig. 4, the processing flows of the initiator system a and the server system B are substantially the same, and if the source file formats of AB are different, only different formats need to be configured for parsing and adapting, and other processing flows are completely the same. Assuming that the A system source file is A.txt and the B system source file is B.txt, the grouped doclets are named by numbers, such as a1. txt.
As shown in fig. 4, the transaction stream splitting data generated by the system a and the system B are distributed to different servers (sub-servers) in pairs, and S102 and S103 are executed by different sub-servers at the same time, and S102 and S103 are the processes which consume the most resources and influence the processing performance most, and they are distributed to a plurality of servers to run, so that distributed computing operation can be implemented to achieve the optimal performance processing under the condition of equal resources. Files distributed to multiple servers only need to be distributed in pairs, for example, a1.txt and b1.txt must be distributed to the same server; however, each server is not required to be allocated only one pair, for example, a1.txt and b1.txt are allocated to the server 1, and a2.txt and b2.txt can also be allocated to the server 1, which requires the allocation scheme to be decided according to the physical resources of the actual server.
Files from the system A and the system B support parallel processing, and because an actual scene cannot ensure that the files of the system A and the system B can arrive at the same time, the system A or the system B is also supported to input a plurality of files, and the files of the same system support serial processing and parallel processing; if parallel processing is required to merge the filtered grouped files into the same group of files, this is not the important point of the present invention, so the parallel mode will not be explained here.
S102: and sorting the transaction flow splitting data according to the key values in the transaction flow splitting data.
In order to improve the reconciliation efficiency, the transaction flow splitting data (small files) needs to be sorted first (all refer to sorting from small to large), but for the data volume of hundreds of millions of levels, even if the total data volume is split into a plurality of small files, the data volume of each small file is still in the tens of millions, if the memory is completely used for sorting, the memory requirement of the system is higher, and even the risk of memory overflow occurs, so that the sorting is carried out by adopting an induction mode. The minimum unit to be processed in this step is a pair of small files, as mentioned above, a1.txt and b1.txt in the result file are a pair, that is, the two systems generate a pair of small files with the same number through step 1, such as an. However, the sorting algorithm is relatively independent, and only the internal data of the same file is sorted, so that the parallel processing of paired files is supported, for example, a1.txt and a2.txt can be simultaneously sorted, and the parallel processing can further improve the processing performance. The elements to be sorted here are for key values only, since this key is a record that identifies uniquely. Parallel means that the induction ordering of all small files supports parallel processing, and the parallelism degree depends on system running resources. The files to be sorted are large, the requirement on resources for sorting when the files are completely loaded into the memory is high, and therefore inductive sorting is used; if the data volume of the grouped small files is small (for example, only tens of thousands of rows of records), the memory can also be directly used for sorting.
Fig. 5 is a flowchart of S102 in the embodiment of the present invention. As shown in fig. 5, S102 includes:
s201: and carrying out secondary splitting on the transaction flow split data to obtain each transaction flow subdata.
FIG. 6 is a schematic diagram of secondary splitting and sorting in an embodiment of the invention. As shown in fig. 6, assuming that the name of the transaction pipeline splitting data to be sorted is c.txt, the transaction pipeline splitting data is split into a plurality of transaction pipeline data, the data size (i.e. the number of records, which needs to be preset, will be identified by "M" here, if M is equal to 100000, it means that every 100000 records are sorted once and output to generate the transaction pipeline data) of each transaction pipeline data can be stored by using a memory,
s202: and sequencing the transaction flow data according to the key values.
In specific implementation, all the split data are read and sequenced line by line, and the smallest line is merged into the last transaction pipeline data file in an additional output mode. Sorting here means reading one element sort once, so it is appropriate to use the "bubble sort" algorithm.
S203: and selecting merged transaction flow data from the first transaction flow data in the sequenced transaction flow sub data according to the key value, and then putting the merged transaction flow data into the transaction flow split data file for corresponding cyclic processing to obtain the sequenced transaction flow split data.
FIG. 7 is a schematic diagram of sorting and merging according to an embodiment of the present invention. As shown in fig. 7, when induction merging is performed, one element is added to perform sorting once, and a bubble sorting algorithm is also used, and then the sorting algorithm of the elements in the memory is not separately described, and the bubble sorting algorithm is uniformly used for sorting from small to large.
Assuming that the transaction pipeline data are c1.txt, c2.txt and … … cn. txt, firstly opening all transaction pipeline data and reading a first row, analyzing to obtain a key and a row record, and putting the key and the row record into a memory in a list manner; sorting all keys from small to large to obtain first element data, namely the element data with the smallest key, outputting row record contents to a result file (transaction stream splitting data) C.txt in an adding mode, and opening a file handle of the C.txt in an adding process without closing; assuming that the record corresponding to the minimum element is key-k, after the key-k is added to the result file, removing the key-k content from the sorted memory, and continuing to read the next line of the ck.txt file, namely the dotted line part in fig. 7, which means that only the next line is read for the ck.txt file, and the next line is not read for other files; txt reads the next line of records and continues to be added into the memory list, and the next line of records is sorted again, namely the minimum element record is obtained again and is additionally output to the result file, and the cycle is performed; if all records of a certain file are processed, the file jumps out of the circulating processing until all files read the tail line, and at the moment, data stored in the memory are sequentially and additionally output to the result file, and then the handle of the result file is closed.
The finally generated C.txt is actually a result file (sequenced transaction stream split data) for sequencing the grouped small files (a1.txt, b1.txt, and the like) split in the first module, and the files generated during the sequencing process, such as c1.txt, c2.txt … …, are only temporary files and can be deleted after the sequencing is finished.
Theoretically, the initiator system a and the server system B need to ensure that the internal data of the provided source files a.txt and b.txt cannot have data of the same key value key (i.e. the same transaction flow cannot have multiple records in the same system), otherwise, in the process of sorting key-1 and key-2 … …, records of the same key need to be removed to account checking difference files. Since this precondition requires source system assurance, the handling of such an exception is not noted in the above flow. That is to say, the c.txt file to be sorted needs to ensure that there is no record of the repeated key value key, otherwise, exception processing of the equivalent key value record needs to be added.
S103: and performing parallel ladder-type reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file.
The transaction pipeline splitting data comprises first transaction pipeline splitting data and second transaction pipeline splitting data.
Assuming that the ordered paired small files (transaction pipeline split data) are A1.txt (first transaction pipeline split data) and B1.txt (second transaction pipeline split data), the checking process is to check the A1.txt and the B1.txt, and the data checking process supports parallel processing and distributed computing.
Fig. 8 is a flowchart of S103 in the embodiment of the present invention. As shown in fig. 8, S103 includes:
s301: and matching the key values of the sorted first transaction pipeline splitting data with the key values of the sorted second transaction pipeline splitting data.
Fig. 9 is a schematic diagram of key value matching in the embodiment of the present invention. As shown in fig. 9, data corresponding to the same key value key is assigned to the same pair of files due to the setting of the grouping algorithm, and the sorted data is also distributed according to the same rule, so the reconciliation can be performed by checking a1.txt and a B1.txt line by line at the same time, and the data on both sides are distributed as if they are a ladder, so the reconciliation is called as a ladder.
In the ladder-type checking process, an account checking result is output, and some result elements, such as total number of successful account checking, total amount of successful account checking, total number of difference and other summary information, are predefined, and are referred to as summary elements hereinafter; it is also necessary to define the difference types, such as: 01-A system single side (i.e. system A has record, system B has no record), 02-B system single side (i.e. system A has no record, system B has record), 03-transaction state does not match, 04-transaction amount is not equal, and difference data format is output to result file.
In specific implementation, file handles of A1.txt and B1.txt are opened, and a first record (represented by a key 1-line record) is read respectively; the key sizes in the key-row record read at A1.txt (the key value is represented by A1-key) and the key-row record read at B1.txt (represented by B1-key) are compared.
S302: and when the matching is successful, checking account according to the account checking content corresponding to the key value to obtain an account checking content split file.
In specific implementation, if the a1-key is equal to the B1-key, elements (account checking contents) which need to be checked, such as transaction states, transaction amounts and the like in the row records, need to be further compared, the elements are respectively accumulated in the summary elements according to the checking results, the difference types and the original data information recorded in the unsuccessful checking records (such as inconsistent amounts and the like) need to be additionally output to the account checking content splitting file, and then the next row of the a1.txt and the B1.txt needs to be respectively read and checked continuously.
S303: and when the matching fails, obtaining a single-side difference split file according to a comparison result of the key values of the sorted first transaction flow split data and the key values of the sorted second transaction flow split data.
In specific implementation, if the A1-key is smaller than the B1-key, the record A system is unilateral, summary elements are accumulated, the A unilateral difference type and the original data information are additionally output to the unilateral difference split file, and at the moment, only the next row of records in the A1.txt file needs to be read and continuously compared and checked with the B1-key; if the A1-key is larger than the B1-key, the record B system is unilateral, summary elements are accumulated, the B unilateral difference type and the original data information are additionally output to a unilateral difference split file, at the moment, the next row of records in the B1.txt file needs to be read, and comparison and check are continuously carried out on the records and the A1-key; traversing the files A1.txt and B1.txt like climbing a ladder until the data reading of one file is finished, taking the rest data of the other file as the single-side data of the system corresponding to the rest files one by one, accumulating the single-side difference of the system, and additionally outputting the single-side difference to a single-side difference split file, wherein for example, after the reading of A1.txt is finished, the rest data of B1.txt are the single-side records of the system B, and the type of the additional difference is also the single side of the system B; and finally, adding the summary element information to the unilateral difference split file, and putting the summary element information as summary result information into a tail line record of the reconciliation result split file.
S304: and splitting the file according to the account checking content and the unilateral difference split file to obtain an account checking result split file.
The ladder check only traverses the paired files once, the algorithm complexity is O (n), while the database check mode needs two-way traversal, and the algorithm complexity is 2 xO (n) 2 ) Therefore, it is necessary to deal with the performanceIs far higher than the common reconciliation mode. Through parallel checking, a plurality of (the number is consistent with the number of the groups) reconciliation result split files, such as C1.txt and C2.txt … …, can be generated.
S104: and sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
In specific implementation, the main server merges reconciliation result split files such as c1.txt and c2.txt, that is, all other records except the last row of summary records are added to one file, such as c.txt. The output differential file format can be customized according to the requirements of the actual scene, and the subsequent processing (such as reconciliation and clearing) of the reconciliation result is out of the scope of the invention.
The execution subject of the distributed reconciliation method shown in fig. 1 can be a branch server. It can be seen from the flow shown in fig. 1 that the distributed reconciliation method according to the embodiment of the present invention sorts according to the key values in the transaction flow split data, performs parallel ladder reconciliation according to the key values in the sorted transaction flow split data and the corresponding reconciliation contents to obtain a reconciliation result split file, and sends the reconciliation result split file to the master server so that the master server merges the reconciliation result split file to obtain the reconciliation result file, and can use low-cost physical resources to achieve the best performance support and adapt to the development of business diversity.
Based on the same inventive concept, the embodiment of the invention also provides a distributed reconciliation device, and as the problem solving principle of the device is similar to that of the distributed reconciliation method, the implementation of the device can refer to the implementation of the method, and repeated parts are not described again.
Fig. 10 is a block diagram of a distributed reconciliation apparatus in an embodiment of the present invention. As shown in fig. 10, the distributed reconciliation apparatus comprises:
the receiving module is used for receiving transaction flow splitting data from the master server; the transaction flow splitting data is generated by splitting the transaction flow data by the total server according to a preset grouping quantity;
the sorting module is used for sorting the transaction flow splitting data according to key values in the transaction flow splitting data;
the reconciliation module is used for carrying out parallel ladder reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file;
and the sending module is used for sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
In one embodiment, the transaction pipeline split data comprises a first transaction pipeline split data and a second transaction pipeline split data;
the reconciliation module comprises:
the matching unit is used for matching the key values of the sorted first transaction pipeline splitting data with the key values of the sorted second transaction pipeline splitting data;
the account checking unit is used for checking the account according to the account checking content corresponding to the key value to obtain an account checking content split file;
the unilateral difference split file unit is used for obtaining a unilateral difference split file according to a comparison result of the key values of the sorted first transaction flow split data and the key values of the sorted second transaction flow split data when matching fails;
and the reconciliation result split file unit is used for splitting the file according to the reconciliation content and the unilateral difference split file to obtain a reconciliation result split file.
In one embodiment, the sorting module comprises:
the secondary splitting unit is used for carrying out secondary splitting on the transaction flow split data to obtain each transaction flow subdata;
the sequencing unit is used for sequencing the transaction flow subdata according to the key values;
and the circulating unit is used for selecting merged transaction flow data from the first transaction flow data in the sequenced transaction flow sub data according to the key value, and then putting the merged transaction flow data into the transaction flow splitting data file for corresponding circulating processing to obtain the sequenced transaction flow splitting data.
To sum up, the distributed reconciliation device of the embodiment of the invention sorts according to the key values in the transaction flow splitting data, performs parallel ladder-type reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation contents to obtain the reconciliation result split file, and sends the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
The embodiment of the present invention further provides a specific implementation manner of a computer device, which can implement all steps in the distributed reconciliation method in the above embodiment. Fig. 11 is a block diagram of a computer device in an embodiment of the present invention, and referring to fig. 11, the computer device specifically includes the following contents:
a processor (processor)1101 and a memory (memory) 1102.
The processor 1101 is configured to call a computer program in the memory 1102, and the processor implements all the steps in the distributed reconciliation method in the above embodiment when executing the computer program, for example, the processor implements the following steps when executing the computer program:
receiving transaction stream splitting data from a master server; splitting the transaction flow splitting data into a total server according to a preset grouping number to generate the transaction flow splitting data;
sorting the transaction flow splitting data according to key values in the transaction flow splitting data;
performing parallel ladder reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file;
and sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
To sum up, the computer device of the embodiment of the present invention sorts according to the key values in the transaction pipeline split data, performs parallel ladder-type reconciliation according to the key values in the sorted transaction pipeline split data and the corresponding reconciliation contents to obtain the reconciliation result split file, and sends the reconciliation result split file to the master server so that the master server merges the reconciliation result split file to obtain the reconciliation result file.
An embodiment of the present invention further provides a computer-readable storage medium capable of implementing all the steps in the distributed reconciliation method in the foregoing embodiment, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements all the steps in the distributed reconciliation method in the foregoing embodiment, for example, when the processor executes the computer program, the following steps are implemented:
receiving transaction stream splitting data from a master server; splitting the transaction flow splitting data into a total server according to a preset grouping number to generate the transaction flow splitting data;
sorting the transaction flow splitting data according to key values in the transaction flow splitting data;
performing parallel ladder reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file;
and sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
To sum up, the computer-readable storage medium of the embodiment of the present invention sorts according to the key values in the transaction pipeline split data, performs parallel ladder-type reconciliation according to the key values in the sorted transaction pipeline split data and the corresponding reconciliation contents to obtain the reconciliation result split file, and sends the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
An embodiment of the present invention further provides a computer program product capable of implementing all the steps in the distributed reconciliation method in the foregoing embodiment, where the computer program product includes a computer program/instruction, and when the computer program/instruction is executed by a processor, the computer program/instruction implements all the steps in the distributed reconciliation method in the foregoing embodiment, for example, when the processor executes the computer program, the processor implements the following steps:
receiving transaction stream splitting data from a master server; splitting the transaction flow splitting data into a total server according to a preset grouping number to generate the transaction flow splitting data;
sorting the transaction flow splitting data according to key values in the transaction flow splitting data;
performing parallel ladder-type reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file;
and sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain the reconciliation result file.
To sum up, the computer program product of the embodiment of the present invention performs sorting according to the key values in the transaction flow splitting data, performs parallel ladder-type reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation contents to obtain the reconciliation result split file, and sends the reconciliation result split file to the master server so that the master server merges the reconciliation result split file to obtain the reconciliation result file.
Based on the same inventive concept, the embodiment of the invention also provides a distributed reconciliation system, and as the problem solving principle of the system is similar to that of the distributed reconciliation method, the implementation of the system can refer to the implementation of the method, and repeated parts are not described again.
Fig. 12 is a schematic diagram of a distributed reconciliation system in an embodiment of the invention. As shown in fig. 12, the distributed reconciliation system comprises:
a plurality of distributed reconciliation devices as described above, which are applied to the sub-servers; and
the main server is used for splitting the transaction flow data according to a preset grouping quantity to obtain transaction flow split data and sending the transaction flow split data to the sub-servers; and merging the reconciliation result split files from the plurality of sub-servers to obtain a reconciliation result file.
The specific working flow of the distributed reconciliation system of the embodiment of the invention is as follows:
1. the main server splits the transaction flow data according to the preset grouping quantity to obtain transaction flow split data, and the transaction flow split data are sent to the sub-servers.
2. And the sub-servers carry out secondary splitting on the transaction flow split data to obtain each transaction flow sub-data, and the transaction flow sub-data is sequenced according to the key values.
3. And the sub-servers select merged transaction flow data from the first transaction flow data in the sequenced transaction flow sub-data according to key values, and then the merged transaction flow data is placed into the transaction flow split data file for corresponding cyclic processing to obtain the sequenced transaction flow split data.
4. The sub-servers match the key values of the sorted first transaction flow splitting data with the key values of the sorted second transaction flow splitting data; when the matching is successful, checking account according to the account checking content corresponding to the key value to obtain an account checking content split file; and when the matching fails, obtaining a single-side difference split file according to a comparison result of the key values of the sorted first transaction flow split data and the key values of the sorted second transaction flow split data.
5. And the sub-server splits the file according to the account checking content and the unilateral difference split file to obtain an account checking result split file.
6. And the sub-servers send the reconciliation result split file to the main server.
7. The general server merges reconciliation result split files from a plurality of sub-servers to obtain a reconciliation result file
In conclusion, the distributed reconciliation system of the embodiment of the invention processes the transaction data based on the file and does not use the database for persistent storage, so that the requirement on database resources is avoided and the hardware cost is greatly saved. The invention realizes the grouped account checking, divides a large data volume, supports parallel and distributed processing by the data processing after division, and can use a plurality of servers with lower resources to check accounts together, thereby improving the account checking efficiency to the maximum extent. The invention adopts a ladder-type method to compare data without repeatedly traversing data and an algorithmThe complexity is O (n), the database checking mode needs two-way traversal, and the algorithm complexity is 2 XO (n) 2 ) Therefore, the efficiency is far higher than that of the database reconciliation scheme. Therefore, the distributed reconciliation system provided by the embodiment of the invention has the following beneficial effects:
1. the account checking is completely carried out based on the files, no database participates, and the database cost can be greatly reduced. In particular, for accounting of large data volume, for hundreds of millions of data, the loading of data by using a single table by using general database resources is impossible.
2. The large file is split into a plurality of small files to process the subsequent key processes, the requirement on the resources (particularly the memory) of the system is low, and the resources can be well distributed.
3. Parallel and distributed computing is supported, the processing performance can be greatly improved by distributing a plurality of servers to support account checking together, and the method is very suitable for the scene of insufficient high-allocation resources.
4. The data checking mode adopts a 'ladder-type' account checking mode, the algorithm complexity is far superior to that of a common database stroke-by-stroke checking mode, and the performance processing is higher.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Those of skill in the art will further appreciate that the various illustrative logical blocks, units, and steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate the interchangeability of hardware and software, various illustrative components, elements, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design requirements of the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present embodiments.
The various illustrative logical blocks, or elements, or devices described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but, in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be located in a user terminal. In the alternative, the processor and the storage medium may reside in different components in a user terminal.
In one or more exemplary designs, the functions described above in connection with the embodiments of the invention may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, such computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store program code in the form of instructions or data structures and which can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Additionally, any connection is properly termed a computer-readable medium, and, thus, is included if the software is transmitted from a website, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wirelessly, e.g., infrared, radio, and microwave. Such discs (disk) and disks (disc) include compact disks, laser disks, optical disks, DVDs, floppy disks and blu-ray disks where disks usually reproduce data magnetically, while disks usually reproduce data optically with lasers. Combinations of the above may also be included in the computer-readable medium.
Claims (10)
1. A distributed reconciliation method, comprising:
receiving transaction stream splitting data from a master server; the transaction flow splitting data is generated by splitting the transaction flow data by the total server according to a preset grouping quantity;
sorting the transaction flow splitting data according to key values in the transaction flow splitting data;
performing parallel ladder-type reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file;
and sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain a reconciliation result file.
2. The distributed reconciliation method of claim 1, wherein the transaction pipeline split data comprises a first transaction pipeline split data and a second transaction pipeline split data;
performing parallel ladder reconciliation according to the key values and the corresponding reconciliation contents in the sorted transaction pipeline split data to obtain a reconciliation result split file comprises the following steps:
matching the key values of the sorted first transaction pipeline splitting data with the key values of the sorted second transaction pipeline splitting data;
when the matching is successful, checking account according to the account checking content corresponding to the key value to obtain an account checking content split file;
when the matching fails, obtaining a single-side difference split file according to a comparison result of the key values of the sorted first transaction flow split data and the key values of the sorted second transaction flow split data;
and splitting the file according to the account checking content and the unilateral difference split file to obtain the account checking result split file.
3. The distributed reconciliation method of claim 1, wherein sorting the transaction pipeline split data according to key values in the transaction pipeline split data comprises:
carrying out secondary splitting on the transaction flow split data to obtain each transaction flow subdata;
sequencing the transaction flow subdata according to the key values;
and selecting merged transaction flow data from the first transaction flow data in the sequenced transaction flow sub data according to the key value, and then putting the merged transaction flow data into the transaction flow split data file for corresponding cyclic processing to obtain the sequenced transaction flow split data.
4. A distributed reconciliation device, comprising:
the receiving module is used for receiving transaction flow splitting data from the master server; the transaction flow splitting data is generated by splitting the transaction flow data by the total server according to a preset grouping quantity;
the sorting module is used for sorting the transaction pipeline split data according to key values in the transaction pipeline split data;
the reconciliation module is used for carrying out parallel ladder reconciliation according to the key values in the sorted transaction flow splitting data and the corresponding reconciliation content to obtain a reconciliation result splitting file;
and the sending module is used for sending the reconciliation result split file to the general server so that the general server merges the reconciliation result split file to obtain a reconciliation result file.
5. The distributed reconciliation apparatus of claim 4 wherein the transaction pipeline split data comprises a first transaction pipeline split data and a second transaction pipeline split data;
the reconciliation module comprises:
the matching unit is used for matching the key values of the sorted first transaction pipeline splitting data with the key values of the sorted second transaction pipeline splitting data;
the account checking unit is used for checking the account according to the account checking content corresponding to the key value to obtain an account checking content split file;
the unilateral difference split file unit is used for obtaining a unilateral difference split file according to a comparison result of the key values of the sorted first transaction flow split data and the key values of the sorted second transaction flow split data when the matching fails;
and the reconciliation result split file unit is used for obtaining the reconciliation result split file according to the reconciliation content split file and the unilateral difference split file.
6. The distributed reconciliation apparatus of claim 4, wherein the ranking module comprises:
the secondary splitting unit is used for carrying out secondary splitting on the transaction flow split data to obtain each transaction flow subdata;
the sequencing unit is used for sequencing the transaction pipeline data according to the key values;
and the circulating unit is used for selecting merged transaction pipeline data from the first transaction pipeline data in the sequenced transaction pipeline data according to the key values, and then putting the merged transaction pipeline data into the transaction pipeline split data file for corresponding circulating processing to obtain the sequenced transaction pipeline split data.
7. A computer device comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that the processor implements the steps of the distributed reconciliation method of any one of claims 1 to 3 when executing the computer program.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the distributed reconciliation method of any one of claims 1 to 3.
9. A computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the steps of the distributed reconciliation method of any one of claims 1 to 3.
10. A distributed reconciliation system, comprising:
a plurality of distributed reconciliation devices according to any one of claims 4 to 6, applied to sub-servers; and
the main server is used for splitting transaction pipeline data according to a preset grouping quantity to obtain transaction pipeline split data and sending the transaction pipeline split data to the sub-servers; and merging the reconciliation result split files from the plurality of sub-servers to obtain a reconciliation result file.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116308850A (en) * | 2023-05-19 | 2023-06-23 | 深圳市四格互联信息技术有限公司 | Account checking method, account checking system, account checking server and storage medium |
| CN117033450A (en) * | 2023-10-10 | 2023-11-10 | 北京轻松怡康信息技术有限公司 | Multi-dimensional data processing method and device, electronic equipment and storage medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116308850A (en) * | 2023-05-19 | 2023-06-23 | 深圳市四格互联信息技术有限公司 | Account checking method, account checking system, account checking server and storage medium |
| CN116308850B (en) * | 2023-05-19 | 2023-09-05 | 深圳市四格互联信息技术有限公司 | Account checking method, account checking system, account checking server and storage medium |
| CN117033450A (en) * | 2023-10-10 | 2023-11-10 | 北京轻松怡康信息技术有限公司 | Multi-dimensional data processing method and device, electronic equipment and storage medium |
| CN117033450B (en) * | 2023-10-10 | 2024-08-30 | 北京轻松怡康信息技术有限公司 | Multi-dimensional data processing method and device, electronic equipment and storage medium |
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